A Novel Method Based on Random Matrix Theory and Mean Shift Clustering for Spectrum Sensing

2021 ◽  
pp. 223-234
Author(s):  
Qiyuan Chen ◽  
Yonghua Wang ◽  
Jiawei Zhuang ◽  
Yi Lyu ◽  
Zhixiong Li
Keyword(s):  
Spectrum Sensing ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Mean Shift ◽  
Mean Shift Clustering ◽  
Novel Method

scholarly journals Spectrum Sensing in Cognitive Radio by Use of Volume-Based Method

2018 ◽  
Vol 7 (2.17) ◽  
pp. 34
Author(s):  
C S. Preetham ◽  
Ch Mahesh ◽  
Ch Saranga Haripriya ◽  
Ramaraju Anirudh ◽  
M S. Sireesha
Keyword(s):  
Covariance Matrix ◽  
Spectrum Sensing ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Sample Covariance Matrix ◽  
Closed Form Expression ◽  
Sample Covariance ◽  
Signal Sample ◽  
Deficiency Cases

Spectrum sensing is the mission of finding the licensed user signal situation, i.e. to determine the existence and deficiency of primary (licensed) user signal, the recent publications random matrix theory algorithms performs better-quality in spectrum sensing. The RMT fundamental nature is to make use of the distributed extremal eigenvalues of the arrived signal sample covariance matrix (SMC), specifically, Tracy-Widom (TW) distribution which is useful to certain extent in spectrum sensing but demanding for numerical evaluations because there is absence of closed-form expression in it. The sample covariance matrix determinant is designed for two novel volume-based detectors or signal existence and deficiency cases are differentiated by using volume. Under the Gaussian noise postulation one of the detectors theoretical decision thresholds is perfectly calculated by using Random matrix theory. The volume-based detectors efficiency is shown in simulation results. 

Cooperative MIMO spectrum sensing based on random matrix theory

2010 ◽  
Vol 27 (2) ◽  
pp. 190-196 ◽  
Author(s):  
Lei Wang ◽  
Baoyu Zheng ◽  
Jingwu Cui ◽  
Chao Chen
Keyword(s):  
Spectrum Sensing ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Matrix Theory ◽  
Cooperative Mimo
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